Statistics

Statistical analysis in a thesis is less about knowing every test than about matching the right test to your data and reporting it in a way a reviewer accepts. The measurement level of your variables, the shape of their distribution and the structure of your hypotheses determine what is legitimate.

These guides work through that sequence in practice — screening and cleaning data, checking assumptions before trusting a result, choosing between parametric and non-parametric tests, running reliability and factor analysis, interpreting regression and structural models, and reporting output with the effect sizes and intervals journals now expect.